Parameter Estimation in Multivariate Gamma Distribution

V. S. Vaidyanathan, R. Vani Lakshmi

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)


Multivariate gamma distribution finds abundant applications in stochastic modelling, hydrology and reliability. Parameter estimation in this distribution is a challenging one as it involves many parameters to be estimated simultaneously. In this paper, the form of multivariate gamma distribution proposed by Mathai and Moschopoulos [9] is considered. This form has nice properties in terms of marginal and conditional densities. A new method of estimation based on optimal search is proposed for estimating the parameters using the marginal distributions and the concepts of maximum likelihood, spacings and least squares. The proposed methodology is easy to implement and is free from calculus. It optimizes the objective function by searching over a wide range of values and determines the estimate of the parameters. The consistency of the estimates is demonstrated in terms of mean, standard deviation and mean square error through simulation studies for different choices of parameters.

Original languageEnglish
Pages (from-to)147-159
Number of pages13
JournalStatistics, Optimization and Information Computing
Issue number2
Publication statusPublished - 2015

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Statistics and Probability
  • Information Systems
  • Computer Vision and Pattern Recognition
  • Statistics, Probability and Uncertainty
  • Control and Optimization
  • Artificial Intelligence


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